Noise characterization of “effective quiet” areas on a U.S. Navy aircraft carrier

The purpose of this investigation was to characterize noise levels in spaces designated as “effective quiet” areas on a U.S. Navy aircraft carrier. Noise dosimetry samples were collected in 15 designated spaces, representing 15 noise measurements, while at-sea during airwing carrier qualifications. Equivalent sound level (L_eq) measurements were collected during flight operations (L_{eq (flt ops)}), non-flight operations (L_{eq (non-flt ops)}), and over 24-hr periods (L_{eq (24-hr)}). These data were compared to the 70 dBA American Conference of Governmental Industrial Hygienists (ACGIH^®) Threshold Limit Value (TLV^®) for “effective quiet” areas intended for temporary threshold shift recovery when personnel live and work in a potentially noise hazardous environment for periods greater than 24?hr. The monitored areas were selected based on personnel occupancy/use during off-duty time periods. Areas were classified by either (1) leisure areas that included mess (eating areas), gyms, lounges, an internet cafe, and the fantail social area or (2) berthing (sleeping) areas. The L_eq measurements in decibels “A” weighted (dBA) were compared to determine significant differences between L_{eq (flt ops)}, L_{eq (non-flt ops)}, and L_{eq (24-hr)} and were compared between leisure area and berthing area. Measured noise levels according to time period ranged as follows: (1) L_{eq (24-hr)}: 70.8–105.4 dBA; (2) L_{eq (flt ops)}: 70–101.2 dBA; and (3) L_{eq (non-flt ops)}: 39.4–104.6 dBA. All area measurements over the 24-hr period and during flight operations and 46.7% of the areas during the non-flight operation time period exceeded the “effective quiet” 70 dBA ACGIH TLV. Mean L_eqs were 15 dBA higher during flight operations compared to non-flight operations in “effective quiet” areas (p?=?0.001). The L_eqs in leisure areas were significantly higher than berthing areas by approximately 21 dBA during non-flight operation periods (p?=?0.001). Results suggest noise levels in “effective quiet” areas frequented by aircraft carrier personnel during off-duty hours when at-sea may inhibit auditory recovery from occupational noise exposures that occur on-duty.     

Twelve tips on setting up and running a peer-led medical education society

Peer-led teaching is an established paradigm with benefits for student teachers, learners and the wider medical community. Students are increasingly taking ownership of such teaching, which has fuelled the creation of new peer-led medical education societies at universities around the UK. Students wishing to undertake such an endeavor must contend with concerns over the quality of peer-led teaching, logistical challenges, lack of senior support and difficulties accessing relevant resources to design and appraise their initiatives. Peer-led medical education societies represent a relatively novel concept, and students may struggle to find practical information on how to approach these challenges. We propose that these obstacles can be overcome by thorough event planning, understanding the role and features of high quality peer-led education in supplementing medical school curricula, maintaining a strong working relationship with local medical faculty, and learning from the wider medical education community.     

Artificial Intelligence and Black‐Box Medical Decisions: Accuracy versus Explainability

Although decision‐making algorithms are not new to medicine, the availability of vast stores of medical data, gains in computing power, and breakthroughs in machine learning are accelerating the pace of their development, expanding the range of questions they can address, and increasing their predictive power. In many cases, however, the most powerful machine learning techniques purchase diagnostic or predictive accuracy at the expense of our ability to access “the knowledge within the machine.” Without an explanation in terms of reasons or a rationale for particular decisions in individual cases, some commentators regard ceding medical decision‐making to black box systems as contravening the profound moral responsibilities of clinicians. I argue, however, that opaque decisions are more common in medicine than critics realize. Moreover, as Aristotle noted over two millennia ago, when our knowledge of causal systems is incomplete and precarious—as it often is in medicine—the ability to explain how results are produced can be less important than the ability to produce such results and empirically verify their accuracy.     

De novo truncating mutation in SCN1A as a cause of febrile seizures plus (FS+)

SCN1A is one of the most relevant epilepsy genes. In general, de novo severe mutations, such as truncating mutations, lead to a classic form of Dravet syndrome (DS), while missense mutations are associated with both DS and milder phenotypes within the GEFS+ spectrum, however, these phenotype‐genotype correlations are not entirely consistent. Case report. We report an 18‐year‐old woman with a history of recurrent febrile generalized tonic‐clonic seizures (GTCS) starting at age four months and afebrile asymmetric GTCS and episodes of arrest, suggestive of focal impaired awareness seizures, starting at nine months. Her psychomotor development was normal. Sequencing of SCN1A revealed a heterozygous de novo truncating mutation (c.5734C>T, p.Arg1912X) in exon 26. Conclusion. Truncating mutations in SCN1A may be associated with milder phenotypes within the GEFS+ spectrum. Accordingly, SCN1A gene testing should be performed as part of the assessment for sporadic patients with mild phenotypes that fit within the GEFS+ spectrum, since the finding of a mutation has diagnostic, therapeutic and genetic counselling implications.     

The case for a medication first approach to the treatment of opioid use disorder

Background: The opioid addiction and overdose crisis continues to ravage communities across the U.S. Maintenance pharmacotherapy using buprenorphine or methadone is the most effective intervention for Opioid Use Disorder (OUD), yet few have immediate and sustained access to these medications. Objectives: To address lack of medication access for people with OUD, the Missouri Department of Mental Health began implementing a Medication First (Med First) treatment approach in its publicly-funded system of comprehensive substance use disorder treatment programs. Methods: This Perspective describes the four principles of Med First, which are based on evidence-based guidelines. It draws conceptual comparisons between the Housing First approach to chronic homelessness and the Med First approach to pharmacotherapy for OUD, and compares state certification standards for substance use disorder (SUD) treatment (the traditional approach) to Med First guidelines for OUD treatment. Finally, the Perspective details how Med First principles have been practically implemented. Results: Med First principles emphasize timely access to maintenance pharmacotherapy without requiring psychosocial services or discontinuation for any reason other than harm to the client. Early results regarding medication utilization and treatment retention are promising. Feedback from providers has been largely favorable, though clinical- and system-level obstacles to effective OUD treatment remain. Conclusion: Like the Housing First model, Medication First is designed to decrease human suffering and activate the strengths and capacities of people in need. It draws on decades of research and facilitates partnerships between psychosocial and medical treatment providers to offer effective and life-saving care to persons with OUD.     

Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials

Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.